As smart phones, personal digital assistants (PDAs), and other mobile devices become increasingly popular, network services applied on mobile devices are growing. Specific network services need to be processed by specific clients, which include applications installed on smart phones.
With the increasing number of social networking sites, more and more users are using social networking sites. When user are using these social networking sites, one of the most common needs is to establish friend relationships based on the social networking sites.
Currently, many social networking sites can provide the functionality of recommending friends for the users, often using following two commonly-used methods.
The first friend-recommendation method includes: a server of a social networking site detects a user's friends list. When detecting that there are two friends in the user's friends list, but these two friends themselves are not mutual friends, the server can recommend one friend of the user to another friend of the user. For example, if user A has two friends, user B and user C, and user B and user C are not friends, the server can recommend user C to user B, or can recommend user B to user C.
The second friend-recommendation method includes: a server of a social networking site detects a user's registration information, such as place of origin, school, hobbies or residence, etc. The server then sends the user friend recommendation information of those that have one or more pieces of same registration information but are not yet the friends of the user. For instance, if user A and user B have same place of origin as Beijing in the registration information, and user A and user B are not friends, then the server can recommend user B to user A, or can recommend user A to user B.
However, under the currently-used friend recommendation methods, when a user receives friend recommendation information, the possibility of receiving recommendation information of a friend of real interest to the user is quite low. For example, the first friend recommendation method may recommend two users without any overlapping to each other. Also for example, when a user's place of origin is Beijing, China, using the second friend recommendation method, the server may send recommendation information of anyone having the place of origin as Beijing, China. Most likely such friend recommendation information is not truly wanted by the user. Therefore, the pool of candidates recommended by the above two methods is too large, and the friend recommendation information generated by these two methods cannot truly reflect the need to establish friend relationships among the users. On one hand, a large amount of friend recommendation information is not wanted by the users and, on the other hand, the server wastes a large amount of bandwidth and storage space in order to push and store such redundant friend recommendation information.
The disclosed methods and systems are directed to solve one or more problems set forth above and other problems.